Peter Dueben from ECMWF gave this talk at the NVIDIA GPU Technology Conference. “Learn how one of the leading institutes for global weather predictions, the European Centre for Medium-Range Weather Forecasts (ECMWF), is preparing for exascale supercomputing and the efficient use of future HPC computing hardware. I will name the main reasons why it is difficult to design efficient weather and climate models and provide an overview on the ongoing community effort to achieve the best possible model performance on existing and future HPC architectures.”

Today NVIDIA released Cuda 9.2, which includes updates to libraries, a new library for accelerating custom linear-algebra algorithms, and lower kernel launch latency. “CUDA 9 is the most powerful software platform for GPU-accelerated applications. It has been built for Volta GPUs and includes faster GPU-accelerated libraries, a new programming model for flexible thread management, and improvements to the compiler and developer tools. With CUDA 9 you can speed up your applications while making them more scalable and robust.”

NCSA is now accepting team applications for the Blue Waters GPU Hackathon. This event will take place September 10-14, 2018 in Illinois. “General-purpose Graphics Processing Units (GPGPUs) potentially offer exceptionally high memory bandwidth and performance for a wide range of applications. A challenge in utilizing such accelerators has been learning how to program them. These hackathons are intended to help overcome this challenge for new GPU programmers and also to help existing GPU programmers to further optimize their applications – a great opportunity for graduate students and postdocs. Any and all GPU programming paradigms are welcome.”

This is the final post in a five-part series from a report exploring the potential machine and a variety of computational approaches, including CPU, GPU and FGPA technologies. This article explores unified deep learning configurations and emerging applications.

One year after launching its cloud service, Nimbus, the Pawsey Supercomputing Centre has now expanded with NVIDIA GPU nodes. The GPUs are currently being installed, so the Pawsey cloud team have begun a Call for Early Adopters. “Launched in mid-2017 as a free cloud service for researchers who require flexible access to high-performance computing resources, Nimbus consists of AMD Opteron CPUs making up 3000 cores and 288 terabytes of storage. Now, Pawsey will be expanding its cloud infrastructure from purely a CPU based system to include GPUs; providing a new set of functionalities for researchers.”

CIARA just announced new AMD-based systems for ultra-low latency, high Frequency Trading and Blockchain solutions. “With the adoption of new technologies such as large core count processors and the usage of ECC memory, the path for all financial enterprises to reap the benefits of safe hardware acceleration without compromising reliability is getting easier,” said Patrick Scateni, Vice President of Enterprise and Performance Group at CIARA. “The joint solutions coming from the CIARA and AMD will bring high-performance and broader choice of compute platforms to the FSI market.”

In this episode of the AI Podcast, Bryan Cantanzaro from NVIDIA discusses some of the latest developments at NVIDIA research. “The goal of NVIDIA research is to figure out what things are going to change the future of the company, and then build prototypes that show the company how to do that,” says Catanzaro. “And AI is a good example of that.”

Today ArrayFire announced the release of ArrayFire v3.6, the company’s open source library of parallel computing functions supporting CUDA, OpenCL, and CPU devices. This new version of ArrayFire includes several new features that improve the performance and usability for applications in machine learning, computer vision, signal processing, statistics, finance, and more. “We use ArrayFire to run the low level parallel computing layer of SDL Neural Machine Translation Products,” said William Tambellini, Senior Software Developer at SDL. “ArrayFire flexibility, robustness and dedicated support makes it a powerful tool to support the development of Deep Learning Applications.”

Jeff Stuecheli from IBM gave this talk at the HPC User Forum in Tucson. “Built from the ground-up for data intensive workloads, POWER9 is the only processor with state-of-the-art I/O subsystem technology, including next generation NVIDIA NVLink, PCIe Gen4, and OpenCAPI.”

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Industry Perspectives

In this podcast, Terri Quinn from LLNL provides an update on Hardware and Integration (HI) at the Exascale Computing Project. "The US Department of Energy (DOE) national laboratories will acquire, install, and operate the nation’s first exascale-class systems. ECP is responsible for assisting with applications and software and accelerating the research and development of critical commercial exascale system hardware. ECP’s Hardware and Integration research focus area (HI), was created to help the laboratories and the ECP teams achieve success through mutually beneficial collaborations." [Read More...]

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A parallel file system offers several advantages over a single direct attached file system. By using fast, scalable, external disk systems with massively parallel access to data, researchers can perform analysis against much larger datasets than they can by batching large datasets through memory. To Learn More about the Parallel File Systems download this guide